Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment

Sadia Samar Ali (), Rajbir Kaur (), D. Jinil Persis (), Raiswa Saha (), Murugan Pattusamy () and V. Raja Sreedharan ()
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Sadia Samar Ali: King Abdulaziz University
Rajbir Kaur: Government Girls College
D. Jinil Persis: National Institute of Industrial Engineering
Raiswa Saha: SRM University
Murugan Pattusamy: University of Hyderabad
V. Raja Sreedharan: Université Internationale de Rabat

Annals of Operations Research, 2023, vol. 324, issue 1, No 10, 249-281

Abstract: Abstract Societal emergence and sustainability are results of human actions and practices which can either imbalance it with maximum exploitation or retain it through responsible utilization of resources. Based on theories on institutional and resource-based views, the study explores the enablers of green sustainable practices of procurement, logistics, product and process design and regulatory frameworks for low carbon performance .The study employs a Hybrid approach of step-by-step empirical process to examine the impact of sustainable practices on low carbon performance which further affects the sustainable manufacturing and societies. A theoretical model developed based on hypothesis is tested first using modified Dillman’s approach. Then it is tested in in the PLS-SEM package using 380 data responses collected from the various manufacturers. Further robustness of proposed model is validated using different ML (machine learning) followed by post hoc analysis using Item Response Theory to validate the scale and efficacy of the measurement model. The study validates the positive relationships of sustainable practices on the low carbon performance which eventually is responsible for sustainable societies. The area of sustainable manufacturing is found relatively lacking and requires further attention of leadership for better societal establishments. The study hopes to further enrich the literature with its unique Hybrid approach of SEM/PLS Machine Learning and IRT which is used to presents carbon performance as a central entity deriving from green practices and driving sustainable manufacturing and societies.

Keywords: Regulatory framework; Low carbon performance; Machine learning; Item response theory; Sustainable society; Sustainable manufacturing (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-020-03877-1

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